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621
Adaptive STATCOM Control for a Multi-machine Power System
Published 2020“…Synchronous static compensator (STATCOM) can be used to improve the dynamic performance of a power system. …”
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622
Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
Published 2018“…In this context, we first propose in this thesis a model providing Intelligent Behavior- Aware Adaptation of Roles using Machine Learning Classification. …”
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masterThesis -
623
Correlation Clustering via 2-Club Clustering with Vertex Splitting
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masterThesis -
624
Area Flexible GF(2k) Elliptic Curve Cryptography Coprocessor
Published 2007“…This multiplier hardware is furthermore adjusted to have area flexibility feature, which is used as the basic block in modeling a complete projective coordinate GF(2k) ECC coprocessor.…”
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625
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626
Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints
Published 2024“…Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …”
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627
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628
Creating and detecting fake reviews of online products
Published 2022“…Using the better model, GPT-2, we create a dataset for a classification task of fake review detection. …”
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629
ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks
Published 2022“…Recently, cognitive network architectures using sophisticated learning techniques are increasingly being applied to such problems. …”
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630
Parallel processing
Published 2005“…The parallel genetic algorithm is based on a model of natural evolution. …”
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conferenceObject -
631
A Novel Centrality-Based Approach for Link Prediction
Published 2025“…Namely, we consider weighted betweenness, closeness and Katz centralities, in addition to the Resource Allocation and Adamic-Adar indices. We also use a genetic algorithm to optimize the weights of these metrics, reflecting their contributions to link prediction. …”
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masterThesis -
632
Defining quantitative rules for identifying influential researchers: Insights from mathematics domain
Published 2024“…The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. …”
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633
Spherical cavity-expansion forcing function in PRONTO 3D for application to penetration problems
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conferenceObject -
634
An automated temporal partitioning tool for a class of DSP applications
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conferenceObject -
635
Investigating the Impact of Skylights and Atrium Configurations on Visual Comfort and Daylight Performance in Dubai Shopping Malls
Published 2025“…Field measurements and computer simulations are conducted to model and validate daylight performance. Annual simulations are used to assess seasonal variations, while sensitivity analysis identifies key parameters. …”
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636
Enhancing e-learning through AI: advanced techniques for optimizing student performance
Published 2024“…The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”
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637
Control of cardiac alternans by mechanical and electrical feedback
Published 2014“…Complimentary to these studies, a three variable Nash-Panfilov model is used to investigate alternans annihilation via mechanical (or stretch) perturbations. …”
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638
Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization
Published 2023“…In particular, the Proximity Policy Optimization (PPO) reinforcement algorithm is used to discover a policy for sensor selection that results in optimum sensor resource allocation. …”
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639
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640
Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose
Published 2020“…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performance of ML algorithms and the models those are trained on drift free data fail to perform on the drifted data. …”